JuDCB:一个基于Julia的动态柱突模拟和曲线拟合框架

IF 10 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
Liangliang Sun, Ming Yong, Meng Tang, Gongkui Xiao, Zhikao Li
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引用次数: 0

摘要

吸附技术在各行各业的清洁生产工作中发挥着关键作用,使其进步对可持续发展至关重要。加强这些过程的可持续性需要可靠和易于使用的建模工具,以尽量减少实验负担并提高能源效率。突破性的模拟和参数拟合对于开发吸附工艺和吸附材料至关重要,使研究人员能够探索各种场景,优化工艺参数,减少实验工作量。然而,目前的仿真工具往往有局限性,包括缺乏灵活性、缺乏透明度、兼容性问题和可用性困难。为了应对这些挑战,我们引入了JuDCB,这是一个用Julia开发的开源框架,它集成了易于使用的高级功能,用于模拟吸附突破曲线和拟合多个参数。JuDCB包括三个主要模块:等温线方程模块,用于选择和评估各种等温线模型;仿真模块,用于执行动态柱突仿真;以及采用进化算法对多个参数进行自主优化的Fitting模块。与依赖手动参数估计或经验相关性的传统方法相比,这种自动拟合方法具有显著的优势。然后,我们将对模型开发和实现进行全面的概述,并提供广泛的教程和案例研究,以说明JuDCB的实用性。该框架的用户友好设计使来自不同学科的研究人员可以访问它,从而促进了材料的快速筛选,并促进了研究和工业应用的进步。JuDCB在GitHub (https://github.com/von19990115/JuDCB)上公开提供。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
JuDCB: A Julia based framework for dynamic column breakthrough simulation and curve fitting
Adsorption technology plays a key role in cleaner production efforts across various industries, making its advancement essential for sustainable development. Enhancing the sustainability of such processes requires reliable and accessible modelling tools that minimise experimental burden and improve energy efficiency. Breakthrough simulations and parameter fitting are essential for developing adsorption processes and adsorbent materials, allowing researchers to explore various scenarios, optimize process parameters, and reduce experimental efforts workload. However, current simulation tools often have limitations including inflexibility, lack of transparency, compatibility problems, and usability difficulties. To address these challenges, we introduce JuDCB, an open-source framework developed in Julia that integrates ease of use with advanced features for simulating adsorption breakthrough curves and fitting multiple parameters. JuDCB consists of three main modules: the Isotherm Equations module for selecting and assessing various isotherm models; the Simulation module for executing dynamic column breakthrough simulations; and the Fitting module that uses an evolutionary algorithm to autonomously optimize multiple parameters. This automated fitting approach provides significant advantages over traditional methods that depend on manual parameter estimation or empirical correlations. We then present a comprehensive overview of the model development and implementation, along with an extensive tutorial and case studies that illustrate the utility of JuDCB. The framework's user-friendly design makes it accessible to researchers from various disciplines, thereby facilitating prompt material screening and fostering advancements in both research and industry applications. JuDCB is made publicly available on GitHub (https://github.com/von19990115/JuDCB).
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来源期刊
Journal of Cleaner Production
Journal of Cleaner Production 环境科学-工程:环境
CiteScore
20.40
自引率
9.00%
发文量
4720
审稿时长
111 days
期刊介绍: The Journal of Cleaner Production is an international, transdisciplinary journal that addresses and discusses theoretical and practical Cleaner Production, Environmental, and Sustainability issues. It aims to help societies become more sustainable by focusing on the concept of 'Cleaner Production', which aims at preventing waste production and increasing efficiencies in energy, water, resources, and human capital use. The journal serves as a platform for corporations, governments, education institutions, regions, and societies to engage in discussions and research related to Cleaner Production, environmental, and sustainability practices.
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